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4. What is Next for Global Climate Modeling?

Global climate modeling has had a long history. With constantly increasing computing capacity, there is the opportunity for adding further complexity and increasing horizontal resolution or decreasing the model grid boxes and the number of vertical layers. Both are being considered and implemented by scientists to make more realistic global climate models.

Transitioning to Earth System Modeling

So far, attempts to model the Earth System have been limited to a few key components—the atmosphere, ocean, land, and sea ice. Some other components like land ice have had to be neglected due to their complexity until now.

Recently, the National Center for Atmospheric Research (NCAR) has released the Community Earth System Model (CESM), an update of what they used to call the Community Climate System Model (CCSM). The name change was largely motivated by the inclusion of a land ice component.

The motivation to go towards Earth System modeling is the realization that the various components are all important and highly integral. Of course, this is not a new realization; this is why ocean, land, and sea ice components were added to the atmosphere. Now, there is an increasing realization that life on Earth also interacts with climate, that as the global climate is warming, the various biomes or regions of unique combinations of plants and animals are changing as well. They are moving poleward or even disappearing altogether. This moves the climate change problem into a global change problem.

The modeling of such interactions needs an ecosystem dynamics model. CESM has options to include a dynamic vegetation model, a model that actually grows vegetation and the interaction between grass, trees, and shrubs, and a land biogeochemistry model, a model that follows carbon and nitrogen through the terrestrial biosphere (Oleson et al. 2010).

Another added complexity to global change modeling is the human component. Humans are substantially changing the landscape with agriculture and urban areas. Croplands have always been defined in climate models, but the characteristics of such land are not constant. Farmers switch out different crops or leave the land to fodder to recuperate nutrients, and in winter, there is generally nothing grown. CESM also includes an option to include a transient land cover prescription (Oleson et al. 2010).

In urban areas, buildings and roadways change the surface energy balance. The fact that cities are warmer than the surrounding countryside is testimony to this. CESM also includes an option to include an urban model which simulates an "urban canyon" with a canyon floor that is divided into components that represent roadways and lawns (Oleson et al. 2010).

The next step is to simulate the interactions of ocean biology with climate. Such interactions would affect not only the carbon cycle but also the energy balance in the ocean. Recent research has shown that the addition of an ocean biogeochemistry model to an ocean GCM warmed SSTs and cooled subsurface temperatures (Nobre et al. 2010, Manizza et al. 2005).

The Need for Increased Resolution

Another problematic feature of global climate models is that they do not have sufficient horizontal and vertical resolution to capture certain weather phenomena like hurricanes. Recent results modeling changes in hurricane occurrence and intensity have been from using climate model simulations as a boundary condition for smaller-scale models in a process known as downscaling that accurately simulate hurricanes (e.g., Emanuel et al. 2008).

However if the resolution of global climate models can be increased substantially, such processes can be then be simulated by the model. The reason for this is the model grid boxes become small enough that physical processes like convection become explicitly rather than implicitly treated.

A group of scientists at a recent meeting, the World Modelling Summit for Climate Prediction (Shukla et al. 2009), had declared the need to increase model resolution to properly simulate such processes. Downscaling to regional model is not sufficient to capture the climate change of small-scale processes, because such models cannot interact global-scale processes.

The Japanese have already had some success with very high-resolution global modeling, but such a model has to use a building-sized supercomputer called the Earth Simulator (Ohfuchi et al. 2007). Such results give us hope that with improvements in computing technology, that such high-resolution modeling will become more easily feasible on smaller-scale supercomputers in the future.

In conclusion, the future looks bright for global climate modeling with the incorporation of more processes and increases in horizontal and vertical resolution. Global climate modeling will remain an integral part of global change research.

References

Emanuel, K., R. Sundararajan, J. Williams, 2008: Hurricanes and global warming. Bulletin of the American Meteorological Society, 89, 347-367.

Manizza, M., C. Le Quéré, A. J. Watson, and E. T. Buitenhuis, 2005: Bio-optical feedbacks among phytoplankton, upper ocean physics and sea ice in a global model. Geophysical Research Letters, 32, L05603, doi:10.1029/2004GL020778.

Nobre, C., G. P. Brasseur, M. A. Shapiro, M. Lahsen, G. Brunet, A. J. Busalacchi, K. Hibbard, S. Seitzinger, K. Noone, and J. P. Ometto, 2010: Addressing the complexity of the Earth System. Bulletin of the American Meteorological Society, 91, 1389-1396.

Ohfuchi, W., H. Sasaki, Y. Masumoto, and H. Nakamura, 2007: "Virtual" atmospheric and oceanic circulation in the Earth Simulator. Bulletin of the American Meteorological Society, 88, 861-866.

Oleson, K. W., and 27 co-authors, 2010: Technical description of version 4.0 of the Community Land Model (CLM). NCAR Technical Note NCAR/TN-478+STR, available at http://www.cesm.ucar.edu/models/cesm1.0/clm/CLM4_Tech_Note.pdf.

Shukla, J., R. Hagedorn, B. Hoskins, J. Kinter, J. Marotzke, M. Miller, T. Palmer, and J. Slingo, 2009: Revolution in climate prediction is both necessary and possible: A declaration at the World Modelling Summit for Climate Prediction. Bulletin ofthe American Meteorological Society, 90, 16-19.

Shukla, J., T. N. Palmer, R. Hagedorn, B. Hoskins, J. Kinter, J. Marotzke, M. Miller, and J. Slingo, 2010: Toward a new generation of world climate research and computing facilities. Bulletin of the American Meteorological Society, 91, 1407-1412.

1. What is Climate?
Radiation: What Drives the Climate
The Components of the Earth System
2. What is a Climate Model?
A Short History of the Development of Climate Models
The Difference Between Climate Modeling and Numerical Weather Prediction
The Ensemble of Climate Models
3. The Components of a Climate Model
Atmospheric Models
Ocean and Sea Ice Models
Land Models
Offline Mode
4. What is Next for Global Climate Modeling?
Transitioning to Earth System Modeling
The Need for Increased Resolution